Supporting data for "zUMIs - A fast and flexible pipeline to process RNA sequencing data with UMIs"
Dataset type: Workflow, Software, Transcriptomic
Data released on May 14, 2018
Parekh S; Ziegenhain C; Vieth B; Enard W; Hellmann I (2018): Supporting data for "zUMIs - A fast and flexible pipeline to process RNA sequencing data with UMIs" GigaScience Database. https://doi.org/10.5524/100447
Single cell RNA-seq (scRNA-seq) experiments typically analyze hundreds or thousands of cells after amplication of the cDNA. The high throughput is made possible by the early introduction of sample-specific barcodes (BCs) and the amplication bias is alleviated by unique molecular identiers (UMIs). Thus the ideal analysis pipeline for scRNA-seq data needs to efficiently tabulate reads according to both BC and UMI. zUMIs is such a pipeline, it can handle both known and random BCs and also efficiently collapses UMIs, either just for Exon mapping reads or for both Exon and Intron mapping reads. Another unique feature of zUMIs is the adaptive downsampling function, that facilitates dealing with hugely varying library sizes, but also allows to evaluate whether the library has been sequenced to saturation. zUMIs flexibility allows to accommodate data generated with any of the major scRNA-seq protocols that use BCs and UMIs. To illustrate the utility of zUMIs, we analysed a single-nucleus RNA-seq dataset and show that more than 35% of all reads map to Introns. We furthermore show that these intronic reads are informative about expression levels, significantly increasing the number of detected genes and improving the cluster resolution.
Additional details
Read the peer-reviewed publication(s):
- Parekh, S., Ziegenhain, C., Vieth, B., Enard, W., & Hellmann, I. (2018). zUMIs - A fast and flexible pipeline to process RNA sequencing data with UMIs. GigaScience, 7(6). https://doi.org/10.1093/gigascience/giy059 (PubMed:29846586)
Additional information:
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Table SettingsFile Name | Description | Sample ID | Data Type | File Format | Size | Release Date | File Attributes | Download |
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Readme | TEXT | 1.75 kB | 2018-04-30 | MD5 checksum: 91ffd59fc36e90f8ee163778409b5eb3 |
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Archival copy of the GitHub repository https://github.com/sdparekh/zUMIs downloaded 30–Apr 2018. zUMIs: A fast and flexible pipeline to process RNA sequencing data with UMIs. Please refer to the GitHub repo for most recent updates. | Mixed archive | archive | 207.94 MB | 2018-04-30 | MD5 checksum: 7a5e8970415c5e90443f6fca7f457971 |
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Data of 96 HEK cells sequenced using the mcSCRB-seq protocol. | Mixed archive | TAR | 71.94 GB | 2018-05-15 | MD5 checksum: 101f0e3598f8a98849b5de29eef0328c |
Funding body | Awardee | Award ID | Comments |
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Deutsche Forschungsgemeinschaft | I Hellmann | SFB1243-A15 | |
Deutsche Forschungsgemeinschaft | W Enard | SFB1243-A14 |
Date | Action |
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May 14, 2018 | Dataset publish |
July 9, 2018 | Manuscript Link added : 10.1093/gigascience/giy059 |
November 11, 2022 | Manuscript Link updated : 10.1093/gigascience/giy059 |